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Description
This roadmap for TVM v0.6. TVM is a community-driven project and we love your feedback and proposals on where we should be heading. Please open up discussion in the discussion forum as well as bring RFCs.
- Feel free to volunteer yourself if you are interested in trying out some items(they do not have to be on the list).
- Please also check out the help wanted list in the github issues on things that need help
Features
- Quantization
- Support for configuring mix-precision
- Per-Channel scale
- Graph packing
- Smarter calibration algorithm
- Model coverage
- Support importing quantization model from other frameworks
- Relay
- Algebra Data Type
- Runtime support for dynamic models
- Support Any syntax
- Pass Manager
- Official text format support
- Automated tuning and scheduling
- graph level automated optimization
- Ultra low-bit support
- tutorials of low-bit ops
- customized accelerator support
- VTA enhancements
- support generic high level models
- Enhanced operator/model coverage
- Ultra-96, ZCU102 support
- Amazon F1 preliminary support
- Low-bit support, bit serial support
- Chisel version
- Micro-asm kernel exploration
- Core micro-asm primitives for certain ops
- Hybrid python programming model
- transition of vision operators to hybrid mode.
- RPC and Device API
- Support a c++ version of cross platform RPC
- Training
- First-order auto differentiation
- Gradient operators
- High-order auto differentiation
- Arithmetics
- Formalize Integer Arithmetic Analysis
- Tutorials
- Tutorials of low-bit ops using Relay
ehsanmok, yidawang, wweic, antinucleon, zhiics and 26 more